This model is a fine-tuned version of PlanTL-GOB-ES/bsc-bio-ehr-es on the Rodrigo1771/combined-train-drugtemist-dev-85-ner dataset. It achieves the following results on the evaluation set:

Loss: 1.1806
Precision: 0.0940
Recall: 0.9540
F1: 0.1711
Accuracy: 0.7890

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 5e-05
train_batch_size: 32
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10.0

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.3191	1.0	541	0.8151	0.0825	0.9605	0.1520	0.7763
0.1619	2.0	1082	0.8332	0.0922	0.9458	0.168	0.7901
0.11	3.0	1623	1.1094	0.0899	0.9494	0.1643	0.7738
0.0764	4.0	2164	1.1206	0.0885	0.9449	0.1618	0.7740
0.0567	5.0	2705	1.1806	0.0940	0.9540	0.1711	0.7890
0.0428	6.0	3246	1.3138	0.0901	0.9458	0.1645	0.7827
0.0332	7.0	3787	1.4009	0.0922	0.9384	0.1679	0.7874
0.0257	8.0	4328	1.5611	0.0904	0.9412	0.1650	0.7791
0.022	9.0	4869	1.5934	0.0921	0.9467	0.1679	0.7835
0.0181	10.0	5410	1.6103	0.0922	0.9439	0.1680	0.7863

Framework versions

Transformers 4.44.2
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.19.1

Rodrigo1771/bsc-bio-ehr-es-combined-train-drugtemist-dev-word2vec-85-ner

output

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Rodrigo1771/
bsc-bio-ehr-es-combined-train-drugtemist-dev-word2vec-85-ner